Rule Extraction from Trained Neural Network Using Genetic Algorithms

摘要

This paper discusses how to extract symbolic rules from a trained artificial neural network (ANN) in domains involving classification using genetic algorithms (GA). Previous methods based on an exhaustive analysis of network connection and output values have already been demonstrated to be intractable in that the scale-up factor increases with the number of nodes and connections in the network. Some experiments are given here.